Paper Citation Record · LEDGER

QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 3 inbound Pith citation observations for arXiv:2508.04974.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.04974 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:40:56.420256Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:45:33.499117Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T14:28:31.443287Z

Reference resolution

3 of 3 outbound references displayed

verified exact0
verified fuzzy2
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fcf74fa-3f19-413c-a111-6b398cbfafaf · outbound

This paper cites However, Gaussians are treated equally weighted for rendering in most 3DGS methods, making them prone to overfitting, which is particularly the case in sparse-view sce- narios.

QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning However, Gaussians are treated equally weighted for rendering in most 3DGS methods, making them prone to overfitting, which is particularly the case in sparse-view sce- narios

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:40:56.874659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 18f942b0-583b-4094-9596-3d5211dfbe73 · outbound

This paper cites 2024; Zhang et al.

QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning 2024; Zhang et al

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:40:56.649010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 73ec29b1-4e99-4c85-abbe-39ac9df2fc36 · outbound

This paper cites UGOD: Uncertainty-Guided Differentiable Opacity and Soft Dropout for Enhanced Sparse-View 3DGS.

QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning UGOD: Uncertainty-Guided Differentiable Opacity and Soft Dropout for Enhanced Sparse-View 3DGS

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T23:40:56.309221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2166d7ff-a767-4601-8014-fe77fc05f9a7 · inbound

Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management cites this paper.

Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:53:08.451502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb3645b8-901b-4880-bcfe-e593f32907be · inbound

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing cites this paper.

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:28:31.444698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b61753ff-9dbc-4227-bbe4-b8f1cd62c588 · inbound

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing cites this paper.

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T11:45:33.499117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.